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We are offering a PhD student position in machine learning (ML) theory, focusing on new methods for training models with a limited amount of data. The student will be a part of a new NEST initiative
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application! This position is in a lab with an interest in many aspects of theoretical ecology (coexistence, niche theory, ecological networks, metacommunities, eco-evolutionary dynamics, and more), where you
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expertise. You will collaborate with other PhD students and postdocs within the group. Our research covers a range of topics—from microbial ecology theory to process engineering. We develop new treatment
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research spans microbial ecology theory to process engineering, and includes the development of new biotechnological processes. Examples of previous research areas include: Anammox Fermentation Microbial
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the intersection of control theory, robotics, artificial intelligence, and signal processing, and is a key enabler of future intelligent infrastructure.This project will focus on the development of novel control
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of robots to interact with the surrounding environment and humans during the execution of specific tasks. Project description The vision of RAI is aiming in closing the gap from theory to real life, while
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of robots to interact with the surrounding environment and humans during the execution of specific tasks. Project description The vision of RAI is aiming in closing the gap from theory to real life, while
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spaces of AI models will be analyzed in their facts using quantitative methods from data science and AI, results of which then be investigated using qualitative methods and theory of critical studies
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Engineering and Autonomous Systems division . We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and learning
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focusing on: Quantum mechanical calculations using density functional theory. Mean-field modeling and Monte Carlo simulations for reaction kinetics. Theoretical spectroscopy By combining quantum mechanical